show(row(box1, box2))
# In[6]:
# 弦图 Chord
chord1 = Chord(data=exercise, source="id", target="kind")
chord2 = Chord(data=exercise, source="id", target="kind", value="pulse")
show(row(chord1, chord2))
# * bokeh.plotting
# In[7]:
from bokeh.plotting import figure
import numpy as np
p = figure(plot_width=400, plot_height=400)
# 方框
p.square(np.random.randint(1, 10, 5),
np.random.randint(1, 10, 5),
size=20,
color="navy")
# 圆形
p.circle(np.random.randint(1, 10, 5),
np.random.randint(1, 10, 5),
size=10,
color="green")
show(p)
#!/usr/local/opt/python3/bin/python3
import pandas
from bokeh.charts import Scatter
from bokeh.plotting import figure, output_file, show
df = pandas.DataFrame(columns=["X-Axis", "Y-Axis"])
df["X-Axis"] = [1, 2, 3, 4, 5]
df["Y-Axis"] = [5, 6, 4, 5, 3]
p = Scatter(df,
x="X-Axis",
y="Y-Axis",
title="Temperature Observations",
xlabel="Day of Observations",
ylabel="Temperature")
output_file("Scatter_charts.html")
show(p)
p = figure(plot_width=500, plot_height=500, title="Earthquakes")
# p.circle([1,2,3,4,5],[3,4,6,1,7],size=12,color="red",alpha=0.5)
# p.triangle([1,2,3,4,5],[3,4,6,1,7],size=12,color="red",alpha=0.5)
# p.circle([1,2,3,4,5],[3,4,6,1,7],size=[8,12,14,16,18],color="red",alpha=0.5)
p.circle([1, 2, 3, 4, 5], [3, 4, 6, 1, 7],
size=[i * 2 for i in [8, 12, 14, 16, 18]],
color="red",
alpha=0.5)
show(p)
output_file("Scatter_plotting.html")
inner="stick")
output_file("Bokeh-ViolinPlot.html")
show(mpl.to_bokeh())
# Gráficos de Linha
from bokeh.plotting import figure, output_file, show
# Outuput
output_file("Bokeh-Grafico-Linha.html")
p = figure(plot_width=400, plot_height=400)
# Adicionando círculos ao gráfico
p.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5)
# Mostrando o resultado
show(p)
# Geojson
from bokeh.io import output_file, show
from bokeh.models import GeoJSONDataSource
from bokeh.plotting import figure
from bokeh.sampledata.sample_geojson import geojson
geo_source = GeoJSONDataSource(geojson=geojson)
p = figure()
p.circle(x='x', y='y', alpha=0.9, source=geo_source)
output_file("Bokeh-GeoJSON.html")
# ----- (2) Test using bokeh.plotting (recommended for more customization) -----
# p = figure(plot_width=500, plot_height=400, title='Earthquake')
p = figure(plot_width=500, plot_height=400)
# help(p)
p.title = 'Earthquake'
p.title_text_color = 'Orange'
p.title_text_font = 'Times'
p.title_text_font_style = 'italic'
p.yaxis.minor_tick_line_color = None
p.xaxis.axis_label = 'Times'
p.yaxis.axis_label = 'Value'
# quad may also be used
p.circle([4, 8, 12], [7, 14, 21], size=17, color='orange', alpha=0.5)
# p.triangle(df['X'], df['Y'], size=10, color='red', alpha=0.5)
p.triangle(df['X'], df['Y'], size=[5, 10, 15, 20, 25], color='red', alpha=0.5)
output_file('Scatter_plotting.html')
# show(p)
# ----- (3) Exercise: Reading from excel -----
df = pandas.read_excel("verlegenhuken.xlsx", sheetname=0)
df["Temperature"] = df["Temperature"]/10
df["Pressure"] = df["Pressure"]/10
p = figure(plot_width=500, plot_height=400, tools='pan,resize', logo=None)
p.title = "Temperature and Air Pressure"
p.title_text_color = "Gray"
